Business process management (BPM) is the discipline of designing, executing, monitoring and improving business processes to achieve organizational goals. BPM has been evolving over the years, from manual workflows to software-based automation, and now to intelligent automation.
Intelligent automation (IA) is the use of automation technologies – artificial intelligence (AI), business process management (BPM), and robotic process automation (RPA) – to streamline and scale decision-making across organizations. IA combines the power of AI, such as natural language processing, computer vision, machine learning and cognitive computing, with the efficiency of RPA, such as bots, scripts and macros, to automate complex and cognitive tasks that require human judgment and interaction.
IA is one of the top technology trends that is transforming BPM in 2023. According to a report by Forbes, IA lies at the intersection of robotics, AI and BPM, and creates smarter business processes and workflows that can incrementally think, learn and adapt as they go. For example, IA can process millions of documents and applications in a day, find errors and suggest fixes or recommendations.
Some of the benefits of IA for BPM are:
- Improved productivity and quality: IA can automate repetitive, rule-based and error-prone tasks, freeing up human workers to focus on more creative and strategic work. IA can also perform tasks faster, more accurately and consistently than humans, reducing errors and rework.
- Enhanced customer experience and satisfaction: IA can provide faster and more personalized service to customers, such as chatbots, voice assistants and self-service portals. IA can also analyze customer feedback and behavior, and provide insights and recommendations to improve customer loyalty and retention.
- Reduced costs and risks: IA can lower operational costs by optimizing resource utilization, reducing waste and increasing efficiency. IA can also mitigate risks by complying with regulations, enforcing policies and detecting fraud and anomalies.
- Increased innovation and agility: IA can enable continuous improvement and learning by analyzing data, identifying patterns and generating insights. IA can also enable rapid adaptation and change by responding to market dynamics, customer needs and business opportunities.
Some of the challenges of IA for BPM are:
- Data quality and availability: IA relies on large volumes of high-quality data to train and operate AI models. However, data may be incomplete, inconsistent, inaccurate or outdated, affecting the performance and reliability of IA solutions.
- Integration and interoperability: IA involves multiple technologies, platforms and systems that need to work together seamlessly. However, integration and interoperability may be difficult due to legacy systems, proprietary standards or incompatible architectures.
- Governance and ethics: IA raises ethical and legal issues such as privacy, security, accountability, transparency and bias. Organizations need to establish clear governance frameworks and policies to ensure that IA solutions are compliant, trustworthy and fair.
To overcome these challenges, organizations need to adopt a holistic approach to implement IA for BPM. Some of the best practices are:
- Define clear objectives and metrics: Organizations need to align their IA initiatives with their business goals and strategies, and define measurable outcomes and indicators to track their progress and performance.
- Assess current processes and capabilities: Organizations need to map their current processes and identify the pain points, gaps and opportunities for improvement. They also need to assess their current capabilities in terms of technology, skills and culture, and identify the gaps and needs for IA adoption.
- Select the right technologies and partners: Organizations need to choose the most suitable technologies and tools for their specific use cases and requirements. They also need to partner with reliable vendors and providers who can offer end-to-end solutions, support and guidance.
- Implement iteratively and incrementally: Organizations need to adopt an agile methodology to implement IA for BPM. They need to start small with pilot projects, test their assumptions and results, learn from feedbacks
Conclusion
The landscape of business process management (BPM) is undergoing a profound transformation through the integration of intelligent automation (IA) technologies. IA, incorporating artificial intelligence (AI), robotic process automation (RPA), and BPM, has paved the way for organizations to streamline their operations, enhance customer experiences, and achieve greater innovation and agility. The benefits of IA in BPM are substantial, including heightened productivity, improved quality, reduced costs, and enhanced customer satisfaction. However, challenges such as data quality, integration complexities, and ethical considerations must be carefully navigated. By following best practices that involve setting clear objectives, evaluating existing processes, choosing appropriate technologies and partners, and implementing iteratively, organizations can unlock the full potential of IA in BPM. As IA continues to mature and evolve, it promises to reshape the way businesses operate and drive them towards a more efficient, customer-centric, and responsive future.